Big Picture

Through MCDC practicums and DAUs (Data Application for Undergraduates) students and faculty have worked on a wide range of data rich projects for various community partners.

Goal

Take these data projects and package them into open lesson plans for instructors to use at various points in a data science course or curriculum.

  1. Re-package the data collection, wrangling, and visualization steps from a project into lessons. Providing a beginning students with a sense of how to breakdown and tackle data projects.

  2. Design lessons that attempt the data projects again.

  3. Create a data repository where instructors can freely access the data and use them in examples or their own lessons. Also, submit to existing data repositories.

The Basics

Instructional Materials are being developed and organized by Professors Lizhen Shi and Arend M Kuyper

GitHub Organization MDCD-Instructional-Materials will host the developed materials which will all have their own GitHub repositories with all supporting documentation

Plan to license under CC BY-SA 4.0 — Creative Commons Attribution-ShareAlike 4.0 International CC BY-SA 4.0

Data Projects

MCDC Data Projects

Some of the data is publicly avialable.

Obtaining permission from a few of the projects.

We plan to make use of as many projects as possible!

Example Lessons

Lessons for Data Science Pathway Courses — Developed by Professor Shi

Results & data from the Equiticity Project

  • Feature Engineering and Time Series Aggregation with Divvy Data

  • Geospatial Visualization with GeoPandas and Folium

  • Enriching Divvy Data with External Datasets for Socio-Spatial Analysis

Distribution Plan

Complete a basic/self-contained release by end of Fall 2025

Post/announce on ASA teaching forums and/or CAUSE

Submit to teaching journals